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Key ResponsibilitiesDesign, develop, and deploy AI orchestration solutions for Generative AI applications.Build AI workflows integrating Snowflake, ML models, LLMs, and unstructured data (RAG).Develop agentic AI solutions using frameworks such as LangChain, LangGraph, Semantic Kernel, or AutoGen.Implement AI best practices including Responsible AI, guardrails, monitoring, and governance.Collaborate with cross-functional teams to deliver scalable AI solutions on Azure.Provide technical leadership, mentorship, and architectural guidance.Must-Have Skills8+ years of Software Engineering, AI, or Machine Learning experience.2+ years in a Technical Lead or Engineering Lead role.Strong experience with Azure OpenAI, Azure ML, Azure Functions, AKS, and Azure services.Experience with Generative AI, LLMs, AI Orchestration, Agentic AI, and RAG.Hands-on experience with LangChain, LangGraph, Semantic Kernel, AutoGen, or similar frameworks.Experience with Snowflake, including Semantic Views and Cortex Analyst.Strong Python programming skills with API and Microservices developmentSolid understanding of MLOps/LLMOps, AI governance, and production AI deployments.Excellent communication and stakeholder management skills.

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Azure Solution Architect / Hands-on Platform Engineer (AI on Azure)
Contract | UK Remote/Hybrid

We're looking for a hands-on Azure Solution Architect who can also operate as a Platform Engineer - someone who can design the target architecture and then get stuck in building it. You'll be working with a delivery team deploying AI capabilities on top of Microsoft Azure in a complex enterprise environment, where governance, security controls and platform customisation are the norm.

This is not a slideware role - you will be engineering day-to-day, automating platform build, enabling secure deployment paths, and supporting teams to run AI workloads reliably in production.

What you'll be doing (hands-on)Building and engineering Azure platform components to support AI workloads (not just documenting them)Implementing enterprise-ready Azure foundations (networking, identity, security, governance)Deploying and operationalising AI services on Azure (eg Azure OpenAI / Azure ML / Cognitive Services)Creating/maintaining IaC and automation for repeatable environments and deploymentsDesigning + implementing secure landing patterns (policy, RBAC, Key Vault, private endpoints)Supporting CI/CD and release processes for platform + AI services (DevOps enablement)Troubleshooting platform/infra issues and improving reliability/observabilityEssential Skills & ExperienceStrong, demonstrable hands-on engineering experience across Azure (build, automate, troubleshoot)Track record as an Azure Solution Architect delivering in enterprise environmentsProven Platform Engineering capability (developer enablement, self-service, automation, standards)Enterprise customisation experience: working around policy constraints, bespoke network/security patterns, governance boardsInfrastructure as Code: Terraform and/or Bicep/ARM (modules, state, pipelines, repeatability)Containers are a strong plus: AKS, Kubernetes, Docker, HelmCI/CD experience: Azure DevOps and/or GitHub ActionsStrong stakeholder skills - but still an engineer who does the workAzure Landing Zones / CAF-aligned platform buildsObservability: Azure Monitor, Log Analytics, App InsightsExperience deploying AI services with private networking/security constraints (enterprise patterns)

Start: ASAP
Location: UK Remote/Hybrid
Duration: Initial 6 months (extensions likely)

Please send across your updated CV if this is of interest

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